Multi-Objective Big Data Optimization with jMetal and Spark

Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi-objective Big Data Optimization problems. Our purpose is to study the influence of accessing data stored in the Hadoop File System (HDFS) in each evaluation step of a metaheuristic and to provide a software tool to solve these kinds of problems. This tool combines the jMetal multi-objective optimization framework with Apache Spark. We have carried out experiments to measure the performance of the proposed parallel infrastructure in an environment based on virtual machines in a local cluster comprising up to 100 cores. We obtained interesting results for computational e ort and propose guidelines to face multi-objective Big Data Optimization problems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

WIELOKRYTERIALNY WYBÓR OPTYMALNYCH OPCJI PROJEKTOWYCH DLA TELEKOMUNIKACJI

The peculiarities of the application of methods of multicriteria optimization in the choice of optimal design options of telecommunication facilities taking into account a set of quality indicators are considered. Examples of multicriteria analysis and the choice of optimal variants for various telecommunication facilities, in particular, the variants of radio network construction of a mobile communication system, the structure and methods of routing in multiservice networks, ad-hoc networks, sensor and actuator networks, as well as mobile communication technologies of the 4th generation are provided.Rozważono osobliwości zastosowania metod optymalizacji wielokryterialnej w wyborze optymalnych opcji projektowych urządzeń telekomunikacyjnych z uwzględnieniem zestawu wskaźników jakości. Podane zostały  przykłady analizy wielokryterialnej i wyboru optymalnych wariantów dla różnych obiektów telekomunikacyjnych, w szczególności wariantów budowy sieci radiowej systemu komunikacji mobilnej, struktury i metod trasowania w sieciach wielousługowych, sieciach ad-hoc, sieciach czujników i urządzeń wykonawczych, a także technologie komunikacji mobilnej czwartej generacji

Practical design of optimal wireless metropolitan area networks: model and algorithms for OFDMA networks

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Ph.D.This thesis contributes to the study of the planning and optimisation of wireless metropolitan area networks, in particular to the access network design of OFDMAbased systems, where different parameters like base station position, antenna tilt and azimuth need to be configured during the early stages of the network life. A practical view for the solution of this problem is presented by means of the development of a novel design framework and the use of multicriteria optimisation. A further consideration of relaying and cooperative communications in the context of the design of this kind of networks is done, an area little researched. With the emergence of new technologies and services, it is very important to accurately identify the factors that affect the design of the wireless access network and define how to take them into account to achieve optimally performing and cost-efficient networks. The new features and flexibility of OFDMA networks seem particularly suited to the provision of different broadband services to metropolitan areas. However, until now, most existing efforts have been focused on the basic access capability networks. This thesis presents a way to deal with the trade-offs generated during the OFDMA access network design, and presents a service-oriented optimization framework that offers a new perspective for this process with consideration of the technical and economic factors. The introduction of relay stations in wireless metropolitan area networks will bring numerous advantages such as coverage extension and capacity enhancement due to the deployment of new cells and the reduction of distance between transmitter and receiver. However, the network designers will also face new challenges with the use of relay stations, since they involve a new source of interference and a complicated air interface; and this need to be carefully evaluated during the network design process. Contrary to the well known procedure of cellular network design over regular or hexagonal scenarios, the wireless network planning and optimization process aims to deal with the non-uniform characteristics of realistic scenarios, where the existence of hotspots, different channel characteristics for the users, or different service requirements will determine the final design of the wireless network. This thesis is structured in three main blocks covering important gaps in the existing literature in planning (efficient simulation) and optimisation. The formulation and ideas proposed in the former case can still be evaluated over regular scenarios, for the sake of simplicity, while the study of latter case needs to be done over specific scenarios that will be described when appropriate. Nevertheless, comments and conclusions are extrapolated to more general cases throughout this work. After an introduction and a description of the related work, this thesis first focuses on the study of models and algorithms for classical point-to-multipoint networks on Chapter 3, where the optimisation framework is proposed. Based on the framework, this work: - Identifies the technology-specific physical factors that affect most importantly the network system level simulation, planning and optimization process. - It demonstrates how to simplify the problem and translate it into a formal optimization routine with consideration of economic factors. - It provides the network provider, a detailed and clear description of different scenarios during the design process so that the most suitable solution can be found. Existing works on this area do not provide such a comprehensive framework. In Chapter 4: - The impact of the relay configuration on the network planning process is analysed. - A new simple and flexible scheme to integrate multihop communications in the Mobile WiMAX frame structure is proposed and evaluated. - Efficient capacity calculations that allow intensive system level simulations in a multihop environment are introduced. In Chapter 5: - An analysis of the optimisation procedure with the addition of relay stations and the derived higher complexity of the process is done. - A frequency plan procedure not found in the existing literature is proposed, which combines it with the use of the necessary frame fragmentation of in-band relay communications and cooperative procedures. - A novel joint two-step process for network planning and optimisation is proposed. Finally, conclusions and open issues are exposed

Holistic, data-driven, service and supply chain optimisation: linked optimisation.

The intensity of competition and technological advancements in the business environment has made companies collaborate and cooperate together as a means of survival. This creates a chain of companies and business components with unified business objectives. However, managing the decision-making process (like scheduling, ordering, delivering and allocating) at the various business components and maintaining a holistic objective is a huge business challenge, as these operations are complex and dynamic. This is because the overall chain of business processes is widely distributed across all the supply chain participants; therefore, no individual collaborator has a complete overview of the processes. Increasingly, such decisions are automated and are strongly supported by optimisation algorithms - manufacturing optimisation, B2B ordering, financial trading, transportation scheduling and allocation. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems like supply chains. It is well-known that decisions made at one point in supply chains can have significant consequences that ripple through linked production and transportation systems. Recently, global shocks to supply chains (COVID-19, climate change, blockage of the Suez Canal) have demonstrated the importance of these interdependencies, and the need to create supply chains that are more resilient and have significantly reduced impact on the environment. Such interacting decision-making systems need to be considered through an optimisation process. However, the interactions between such decision-making systems are not modelled. We therefore believe that modelling such interactions is an opportunity to provide computational extensions to current optimisation paradigms. This research study aims to develop a general framework for formulating and solving holistic, data-driven optimisation problems in service and supply chains. This research achieved this aim and contributes to scholarship by firstly considering the complexities of supply chain problems from a linked problem perspective. This leads to developing a formalism for characterising linked optimisation problems as a model for supply chains. Secondly, the research adopts a method for creating a linked optimisation problem benchmark by linking existing classical benchmark sets. This involves using a mix of classical optimisation problems, typically relating to supply chain decision problems, to describe different modes of linkages in linked optimisation problems. Thirdly, several techniques for linking supply chain fragmented data have been proposed in the literature to identify data relationships. Therefore, this thesis explores some of these techniques and combines them in specific ways to improve the data discovery process. Lastly, many state-of-the-art algorithms have been explored in the literature and these algorithms have been used to tackle problems relating to supply chain problems. This research therefore investigates the resilient state-of-the-art optimisation algorithms presented in the literature, and then designs suitable algorithmic approaches inspired by the existing algorithms and the nature of problem linkages to address different problem linkages in supply chains. Considering research findings and future perspectives, the study demonstrates the suitability of algorithms to different linked structures involving two sub-problems, which suggests further investigations on issues like the suitability of algorithms on more complex structures, benchmark methodologies, holistic goals and evaluation, processmining, game theory and dependency analysis